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27221 - 27230 von 32521

	27221	Modeling the compressive strength of concrete at different curing regimes using machine learning Enthalten in Discover sustainability Bd. 6, 1.5.2025, Nr. 1, date:12.2025: 1-26
	27222	Modeling the gasification process in producing raw gases and solids using machine learning techniques in combination with optimization algorithms Enthalten in Multiscale and multidisciplinary modeling, experiments and design Bd. 8, 26.11.2024, Nr. 1, date:1.2025: 1-22
	27223	Modeling the indoor temperature depending on insulation thickness using machine learning methods Enthalten in The European physical journal / Plus Bd. 139, 9.10.2024, Nr. 10, date:10.2024: 1-17
	27224	Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms Enthalten in Scientific reports Bd. 15, 1.7.2025, Nr. 1, date:12.2025: 1-11
	27225	Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state Enthalten in Scientific reports Bd. 12, 2.9.2022, Nr. 1, date:12.2022: 1-25
	27226	Modeling the spatial variation of calcium carbonate equivalent to depth using machine learning techniques Enthalten in Environmental monitoring and assessment Bd. 195, 25.4.2023, Nr. 5, date:5.2023: 1-16
	27227	Modeling the trend of coronavirus disease 2019 and restoration of operational capability of metropolitan medical service in China: a machine learning and mathematical model-based analysis Enthalten in Global health research and policy Bd. 5, 6.5.2020, Nr. 1, date:12.2020: 1-11
	27228	Modeling the Vibrational Relaxation Rate Using Machine-Learning Methods Enthalten in Sankt-Peterburgskij gosudarstvennyj universitet: Vestnik / Mathematics Bd. 55, 6.6.2022, Nr. 1, date:3.2022: 87-95
	27229	Modeling the viscoelastic behavior of a FG nonlocal beam with deformable boundaries based on hybrid machine learning and semi-analytical approaches Enthalten in Archive of applied mechanics Bd. 95, 20.3.2025, Nr. 4, date:4.2025: 1-32
	27230	Modeling Traffic Crashes on Rural and Suburban Highways Using Ensemble Machine Learning Methods Enthalten in Taehan-t'omok-hakhoe: KSCE journal of civil engineering Bd. 27, 19.11.2022, Nr. 2, date:2.2023: 814-825

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